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A Recursive Programming Model of Farm Growth in Northern Germany

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  • Theodor Heidhues

Abstract

This article develops a recursive programming model of individual farm changes which includes explicitly savings, investments, and growth. Recursive programming as a sequential optimizing rule with a functional relationship between any given period and preceding periods permits the analysis of dynamic properties of adjustment processes. This model emphasizes the behavioral and objective structure of the money capital and investment constraints. The evaluation of growth possibilities is based on the ability of farms to accumulate investment capital relative to the investment needs projected by the model. The model was used to analyze the effects of four EEC policy alternatives on different types of farms in Northern Germany between 1964–65 and 1969–70. The assumed changes in prices and price ratios for agricultural products, in particular for grain, livestock, and milk, affect the projected annual farm income strongly; they lead to moderate shifts between various enterprises; yet the overall growth pattern as characterized by the introduction of new technology and capital-labor substitution is remarkably similar under all alternatives.

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  • Theodor Heidhues, 1966. "A Recursive Programming Model of Farm Growth in Northern Germany," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 48(3_Part_I), pages 668-684.
    • Handle: RePEc:oup:ajagec:v:48:y:1966:i:3_part_i:p:668-684.
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    File URL: http://hdl.handle.net/10.2307/1236868
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    Cited by:

    1. King, Robert P., 1979. "Operational Techniques for Applied Decision Analysis Under Uncertainty," AAEA Fellows - Dissertations and Theses, Agricultural and Applied Economics Association, number 181951, December.
    2. Walker, Odell L. & Hardin, Mike L. & Mapp, Harry P., Jr. & Roush, Clint E., 1979. "Farm Growth And Estate Transfer In An Uncertain Environment," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 11(1), pages 1-12, July.
    3. Balmann, Alfons & Happe, Kathrin, 2001. "Agentenbasierte Politik- und Sektoranalyse - Perspektiven und Herausforderungen," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 50(08), pages 1-12.
    4. El-Kheshan, Kamal & Howitt, Richard & Goueli, Ahmed & Jones, G. T., 1983. "Regional Land and Water Utilization in Egypt: An Empirical Estimation of Opportunity Costs," Working Papers 243851, University of California, Davis, Agricultural Development Systems: Egypt Project.
    5. Rafeld, Frederick J. & Shaudys, Edgar T., 1970. "Empirical Testing Of A Farm Firm Growth Theory," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 2(1), pages 1-5, December.
    6. Robert, Marion & Thomas, Alban & Sekhar, Muddu & Badiger, Shrinivas & Ruiz, Laurent & Raynal, Hélène & Bergez, Jacques-Eric, 2017. "Adaptive and dynamic decision-making processes: A conceptual model of production systems on Indian farms," Agricultural Systems, Elsevier, vol. 157(C), pages 279-291.
    7. Renborg, Ulf, 1970. "Growth of the Agricultural Firm: Problems and Theories," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 38(02), pages 1-51, June.
    8. Runge, C. Ford, 2006. "Agricultural Economics: A Brief Intellectual History," Staff Papers 13649, University of Minnesota, Department of Applied Economics.

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